As exemplary harvesting machines having an on-board packaging capability for the purposes of explaining the present invention, cotton harvesters including on-board cotton module builders or packagers are typically used to create cotton modules having a generally rectangular shape, conforming to specific dimensions to facilitate handling and transporting on dedicated transport vehicles and processing by gins. The most accepted and recognized of the known on-board cotton module builders utilize an accompanying unloading door or ramp, which unfolds as the cotton module builder is tilted, for providing a continuous, level surface extending from the floor of the builder to the ground or other surface onto which the cotton module is to be unloaded. The cotton module is moved along the ramp by a suitable driver system which may include one or more powered drag chains, belts, rollers, or the like.
Often the cotton modules are unloaded by the harvester in or near the swath of field from which the cotton was harvested. Also commonly, at a later time a transport vehicle with a holding area and loading and unloading structure collects the cotton modules and transports them from their various locations in the field and unloads them at another location to await transport to a storage location, or cotton gin or processing facility for further processing, or unloads them at the gin or processing facility. It is not uncommon for a cotton module to be transported several times prior to reaching the gin.
It is desirable to be able to record, correlate, and analyze information associated with a crop at various phases of production, such as planting, growing, harvesting, transporting, processing, or classifying, for analysis and use in decision making and valuation for the current season and future seasons. One crop attribute of particular importance is yield value, or quantity of crop harvested from a particular area, e.g. kilograms/hectare, pounds/acre, metric tons/hectare, bushels/acre, and the like. An accurate cotton yield monitor system on or associated with the harvester can provide information that is useful to keep track of yields on-the-go, e.g., while harvesting and in-transit, for instance, for planning drop-off and collection locations for completed modules. The typical yield monitor system includes a sensor or group of sensors installed on the vehicle, provides estimated yield data based on sensed conditions, and if it generates reasonably accurate yield data, is valuable to dynamically measure spatial yield variability for developing yield maps of a field. However, it is understood that yield maps will only be as accurate as the yield data inputs. Also, by observing and analyzing the yield variability across a field, in-field harvester adjustments can be made to improve present yield and informed decisions made to improve future productivity.
As is evident, the accuracy of the yield monitor system is very important in this process. But the accuracy of the system must be considered in light of the measurement sample. For example, instantaneous accuracy refers to the accuracy of each measured data point, load accuracy refers to the accuracy for a load or a specified number of cotton modules, and field accuracy refers to the accuracy of the yield monitor during the harvest of the entire field. Shortcomings include that instantaneous accuracy is difficult to measure, and field accuracy may be misleading because measurement errors in opposite directions tend to average out, possibly creating a misleading measure of accuracy for the field monitor system. Therefore, there is a tendency to use the measured quantity, mass, or weight of a load (e.g. kilograms, pounds, tons, bushels, etc) when determining if, and when, the yield monitor system needs to be calibrated.
As one known manner to determine load accuracy, a load of cotton is harvested and packaged, e.g., into a discrete module, and once processed, the yield monitor information for that package is compared with the more accurately measured yield data from the gin or processing or receiving facility. There is obviously an inherent delay between harvesting and receiving gin data to calibrate the yield monitor. In the interim, a significant amount of cotton may have been harvested and packaged with yield data collected using an improperly calibrated yield monitor. As a consequence, during this time any in-field decisions were based on inaccurate data.
Efforts to eliminate the time delay include using a measuring or sensing device in the field, e.g., a scale. In this scenario, a load or package of cotton is loaded into or onto the sensing device and measured. The yield monitor information is compared with the sensing device information. Based on the result of the comparison, the yield monitor information may be modified and/or the yield monitor system may be calibrated. An advantage of this process is that it reduces the time delay associated with the data comparison. As a disadvantage, it adds a harvesting delay and increases the labor and equipment costs. It also adds a possible source of error or errors in the measuring or sensing device.
A significant consequential problem that can be created is that this new source of error may be difficult or impossible to discern from the yield monitor system errors. For example, one source of error in the yield monitor system is the build-up of dust, residue, or lint on optical sensors associated with the picker chutes of a harvester. If the sensors become partially blocked or fully blocked, the flow rates measured thereby will include inaccuracy. In addition, this inaccuracy may increase gradually as the harvester is moving through the field or it may suddenly clear after the harvester passes over uneven terrain and the build-up on the sensors falls away, or the sensor is cleaned.
Accordingly, what is sought is a system and method for automatically updating estimated yield values and improving the accuracy of a yield monitor system, which overcomes at least one of the problems, shortcomings or disadvantages as set forth above.